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4 days ago
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Requirements and responsibilities
Overall & Domain Experience: 8+ years of proven software engineering experience, with a substantial and dedicated focus on building, evaluating, and scaling AI/ML systems in production.Framework Mastery: Deep, hands-on production experience with LangChain and LangGraph for managing complex state machines and cyclic agent execution paths.Agentic AI & Protocol Standards: Strong understanding of autonomous tool-calling loops, multi-agent collaboration patterns, and direct experience implementing the Model Context Protocol (MCP).RAG Architectures: Exceptional command over vector databases (e.g., Pinecone, Milvus, pgvector, OpenSearch), embeddings, text chunking strategies, and retrieval evaluation metrics.AWS Ecosystem: Deep technical competency across AWS services?specifically containerized deployments on Amazon EKS/Kubernetes, S3 data management, IAM security policies, and foundational AI tools.Core Languages: Expert-level proficiency in Python and its scientific stack (NumPy, Pandas, PyTorch/TensorFlow).Preferred QualificationsAI Governance Expertise: Prior experience implementing automated auditing, bias detection, and lineage tracking for generative AI systems inside heavily regulated environments (e.g., BFSI, Insurance, Healthcare).Production Maturity: A proven track record of moving agentic systems out of the local notebook phase and successfully scaling them into stable, monitored, low-latency microservices.Mandatory Skills: Agentic AI, Python, RAG, LLM, AWS
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